People & perspective
Keep people at the center of intelligent automation.
Automation works best when it gives people more clarity and control. Use AI to gather context and prepare routine work, while preserving human review for consequential decisions. Make proposed actions visible and give reviewers a practical way to understand, adjust, or reject them.
Begin with the human bottleneck
Automation projects often start with a list of tasks that could be faster. A more useful starting point is the work that makes people feel stuck: gathering the same information repeatedly, interpreting an unclear request, or checking several systems before a decision.
In a fictional service team, an assistant could assemble the history of a support request before a specialist opens it. The purpose is not to replace that specialist’s judgment. It is to give them a better starting point and more time for the part of the work that needs attention.
Define what the assistant may do
Separate preparation, recommendation, and execution. Summarizing a request is different from recommending a response, and both are different from sending it. Each stage needs a clear boundary so users understand what has happened and what still requires their input.
Start with a narrow task and an explicit reviewer. Show the source material used for a summary and make missing context visible. If the assistant cannot determine an answer, it should leave the question open rather than make uncertainty disappear behind confident wording.
Make correction part of the interface
People need to inspect, edit, reject, and rerun automated work without losing their own changes. A reviewer should be able to see the proposed action and understand its effect before confirming it. Where practical, keep a record of the approved version and the person responsible.
Treat corrections as valuable feedback. If reviewers repeatedly rewrite the same part of a draft, investigate whether the instructions, source material, or task boundaries need improvement. Asking people to quietly repair the same mistake every day is not a successful automation.
Measure usefulness as well as speed
Observe how much review a task needs, how often the output is accepted, and whether users can explain the result. A fast draft that takes longer to verify may not improve the overall experience. Include the reviewer’s effort when evaluating the workflow.
Expand only after the narrow use case is dependable enough for its purpose. Keep human ownership visible as the system grows. Good automation gives people a clearer view of their work and more room to exercise judgment, not another opaque process to supervise.